System for simulating molecular interactions involved in inflammation

Abstract

The present invention relates to the filed of simulation of molecular interactions for assessing diseases and disease therapies. In particular, it relates to a system for simulating molecular interactions involved in inflammation in a subject, said system comprising a processing unit comprising a database comprising a plurality of datasets each comprising at least an identifier for a molecule suspected to be involved in the pathological process, data on molecular interactions of the said molecule with one or more other molecule, and at least one data characteristic that is allocated to the dataset, wherein each dataset has at least one relation with another dataset in the database based on molecular interactions, wherein the datasets are grouped into data compartments comprising datasets having identical data characteristics, and wherein the data characteristics are indicative for the biological function of a molecule in inflammation, and an computer program-based algorithm implemented in the processing unit which generates a network map based on the plurality of datasets in the database and which allows for identifying nodes within network map based on predefined parameters, and a visualization unit which allows for determination of the molecular interactions in the identified nodes. Moreover, the present invention contemplates a method for simulating molecular interactions involved in inflammation in a subject as well as the use of the system of the invention for simulating molecular interactions involved in inflammation.

1 . A system for simulating molecular interactions involved in inflammation in a subject, said system comprising
 (I) a processing unit comprising
 (a) a database comprising a plurality of datasets each comprising
 (i) at least an identifier for a molecule suspected to be involved in the pathological process, 
 (ii) data on molecular interactions of the said molecule with one or more other molecule, and 
 (iii) at least one data characteristic that is allocated to the dataset, 
 wherein each dataset has at least one relation with another dataset in the database based on molecular interactions; 
 wherein the datasets are grouped into data compartments comprising datasets having identical data characteristics; and 
 wherein the data characteristics are indicative for the biological function of a molecule in inflammation; 
 and 
 
 (b) an computer program-based algorithm implemented in the processing unit which generates a network map based on the plurality of datasets in the database and which allows for identifying nodes within network map based on predefined parameters; and 
   (II) a visualization unit which allows for determination of the molecular interactions involved in inflammation in the identified nodes.   
     
     
         2 . The system of  claim 1 , wherein said inflammation comprises inflammation resolution. 
     
     
         3 . The system of  claim 1 , wherein said molecule is identified from a damage associated molecular pattern (DAMP) or from a pathogen associated molecular pattern (PAMP). 
     
     
         4 . The system of  claim 3 , wherein said DAMP and/or said PAMP are derived from evaluation of publications in public scientific databases using an automated evaluation algorithm which identifies molecules suspected to be involved in inflammation. 
     
     
         5 . The system of  claim 1 , wherein said biological function of a molecule in inflammation is selected from the group consisting of: Mast Cell degranulation, Macrophage Differentiation, Myeloid Cell Differentiation, Lymphocyte Differentiation, Immune Cell Differentiation, Regulation of Hemopoiesis, Initiation of Innate Immune Response, Pattern recognition Receptor Signaling Pathways, Cytokine Production, Regulation of Adaptive Immune Responses, T-cell Mediated Immune Response, T cell Selection, Regulation of B cell Proliferation, Regulation of Immunoglobulin Secretion, Regulation of T cell Proliferation, Regulation of Lymphocyte Proliferation, Inflammation Resolution, Gene Expression Regulation, Protein Modification, Blood Vessel Development, Immune Response, Hemopoiesis, Neuronal Development, and Protein Transport. 
     
     
         6 . The system of  claim 1 , wherein said computer program-based algorithm implemented in the processing unit which generates a network map based on the plurality of datasets in the database and which allows for identifying nodes within network map comprises rules for gene prioritization, determining node degree, determining betweennecess centrality, motif identification, in particular, identification of feedback or feedforward loops, and/or determining association with inflammation. 
     
     
         7 . The system of  claim 1 , wherein transcriptomics data obtained from the subject after administration of a drug are also provided in the database. 
     
     
         8 . The system of  claim 7 , wherein the transcriptomics data are used to model the datasets in the database. 
     
     
         9 . The system of  claim 8 , wherein datasets from the database are eliminated if no match is found between the identifier for a molecule in the dataset and the molecule identifier in the transcriptomics data. 
     
     
         10 . The system of  claim 7 , wherein said drug is a multicomponent drug. 
     
     
         11 . The system of  claim 10 , wherein said multicomponent drug is Traumeel. 
     
     
         12 . The system of  claim 1 , wherein the visualization unit comprises a computer program-based algorithm which graphically arranges highly connected nodes close to each other and/or which identifies only nodes for graphical display that are intramodularly connected. 
     
     
         13 . A method for simulating molecular interactions involved in inflammation in a subject, said method comprising
 (I) providing a processing unit comprising
 (a) a database comprising a plurality of datasets each comprising
 (i) at least an identifier for a molecule suspected to be involved in the pathological process, 
 (ii) data on molecular interactions of the said molecule with one or more other molecule, and 
 (iii) at least one data characteristic that is allocated to the dataset, 
 wherein each dataset has at least one relation with another dataset in the database based on molecular interactions; 
 wherein the datasets are grouped into data compartments comprising datasets having identical data characteristics; and 
 wherein the data characteristics are indicative for the biological function of a molecule in inflammation; 
 and 
 
 (b) an computer program-based algorithm implemented in the processing unit which generates a network map based on the plurality of datasets in the database and which allows for identifying nodes within network map based on predefined parameters; 
   (II) generating a network map based on the plurality of datasets in the database and identifying nodes within network map based on predefined parameters by executing the computer program-based algorithm implemented in the processing unit; and   (III) determining molecular interactions involved in inflammation in the identified nodes by using a visualization unit whereby the molecular interactions involved in inflammation in a subject are simulated.   
     
     
         14 . The method of  claim 13 , wherein said inflammation comprises inflammation resolution. 
     
     
         15 . The method of  claim 13 , wherein said molecule is identified from a damage associated molecular pattern (DAMP) or from a pathogen associated molecular pattern (PAMP). 
     
     
         16 . The method of  claim 15 , wherein said DAMP and/or said PAMP are derived from evaluation of publications in public scientific databases using an automated evaluation algorithm which identifies molecules suspected to be involved in inflammation. 
     
     
         17 . The method of  claim 13 , wherein said biological function of a molecule in inflammation is selected from the group consisting of: Mast Cell degranulation, Macrophage Differentiation, Myeloid Cell Differentiation, Lymphocyte Differentiation, Immune Cell Differentiation, Regulation of Hemopoiesis, Initiation of Innate Immune Response, Pattern recognition Receptor Signaling Pathways, Cytokine Production, Regulation of Adaptive Immune Responses, T-cell Mediated Immune Response, T cell Selection, Regulation of B cell Proliferation, Regulation of Immunoglobulin Secretion, Regulation of T cell Proliferation, Regulation of Lymphocyte Proliferation, Inflammation Resolution, Gene Expression Regulation, Protein Modification, Blood Vessel Development, Immune Response, Hemopoiesis, Neuronal Development, and Protein Transport. 
     
     
         18 . The method of  claim 13 , wherein said generating a network map based on the plurality of datasets in the database and identifying nodes within network map comprises gene prioritization, determining node degree, determining betweennecess centrality, motif identification, in particular, identification of feedback or feedforward loops, and/or determining association with inflammation. 
     
     
         19 . The method of  claim 13 , wherein transcriptomics data obtained from the subject after administration of a drug are also provided in the database. 
     
     
         20 . The method of  claim 19 , wherein the transcriptomics data are used to model the datasets in the database. 
     
     
         21 . The method of  claim 20 , wherein datasets from the database are eliminated if no match is found between the identifier for a molecule in the dataset and the molecule identifier in the transcriptomics data. 
     
     
         22 . The method of  claim 19 , wherein said drug is a multicomponent drug. 
     
     
         23 . The method of  claim 22 , wherein said multicomponent drug is Traumeel. 
     
     
         24 . The method of  claim 13 , wherein the visualization unit comprises a computer program-based algorithm which graphically arranges highly connected nodes close to each other and/or which identifies only nodes for graphical display that are intramodularly connected. 
     
     
         25 . A method of using the system of  claim 1 , for simulating molecular interactions involved in inflammation in a subject. 
     
     
         26 . The method of  claim 25 , wherein simulating molecular interactions involved in inflammation in a subject is applied for determining drug actions.